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| Title: |
Multi-label classification of music by emotion |
| Author(s): |
K. Trohidis, G. Tsoumakas, G. Kalliris, I. Vlahavas.
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| Availability: |
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| Keywords: |
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| Appeared in: |
EURASIP Journal on Audio, Speech, and Music Processing, 2011:4, 2011.
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| Abstract: |
This work studies the task of automatic emotion detection in music. Music may
evoke more than one different emotion at the same time. Single-label classification and
regression cannot model this multiplicity. Therefore, this work focuses on multi-label
classification approaches, where a piece of music may simultaneously belong to more
than one class. Seven algorithms are experimentally compared for this task.
Furthermore, the predictive power of several audio features is evaluated using a new
multi-label feature selection method. Experiments are conducted on a set of 593 songs
with six clusters of emotions based on the Tellegen-Watson-Clark model of affect.
Results show that multi-label modeling is successful and provide interesting insights
into the predictive quality of the algorithms and features. |
| See also : |
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